Step 1:Download packages
library(mosaic)
library(DataComputing)
library(tidyverse)
library(mosaicData)
library(dplyr)
library("rjson")
Step 2:Importing and preparing data
Canada <- read.csv("CAvideos.csv")
US <- read.csv("USvideos.csv")
GreatBritain <- read.csv(("GB.csv"))
Step 3:Look at the datatable by using summary functions
head(Canada)
tail(US)
names(GreatBritain)
[1] "video_id" "trending_date" "title" "channel_title"
[5] "category_id" "publish_time" "tags" "views"
[9] "likes" "dislikes" "comment_count" "thumbnail_link"
[13] "comments_disabled" "ratings_disabled" "video_error_or_removed" "description"
[17] "X" "X.1" "X.2" "X.3"
[21] "X.4" "X.5" "X.6" "X.7"
[25] "X.8" "X.9" "X.10" "X.11"
[29] "X.12" "X.13" "X.14" "X.15"
[33] "X.16" "X.17" "X.18" "X.19"
[37] "X.20" "X.21" "X.22" "X.23"
[41] "X.24" "X.25"
Step 4:Data Wrangling
GreatBritain <-
GreatBritain %>%
select(title,publish_time,channel_title,category_id,publish_time,tags,views,likes,dislikes,comment_count,thumbnail_link,description)
GreatBritain %>%
filter(category_id == 10)